AWS Public Sector Blog
Category: Amazon QuickSight
Analyzing vehicle fleet location data from a data lake with AWS
At AWS, many public sector customers operate fleets of vehicles (e.g. emergency response, public transportation) that generate location data, which is ultimately stored in a data lake. These customers frequently ask how they can quickly visualize this data and extract insights that can help them optimize how they operate their vehicle fleets. In this post, learn how to use Amazon Athena and Amazon Location Service to perform ad hoc reverse geocoding on a notional dataset of vehicle location history, and visualize the results on an Amazon QuickSight map.
A Texas regional education service center’s cloud journey starts with Amazon QuickSight
Texas Region 4 ESC (TX-Region 4) is a regional education service center that offers a range of services that help K12 education organizations improve student performance, enable faculty success, and implement state initiatives. When TX-Region 4 wanted to migrate its business intelligence (BI) solution to the cloud, they turned to AWS and Amazon QuickSight to save time and produce more insights to better their educational offerings.
Generating program-defining insights in seconds for child, adult, senior, and military services
Easterseals, DC MD VA is a multifaceted nonprofit organization with the goal of enriching lives and expanding opportunities for children and adults in the Washington DC, Maryland, and Virginia (DMV) area, including people with disabilities and military backgrounds. With support from our account team at AWS, Easterseals established a data lake to better understand and define the impact our organization has on its participants with the overarching goal of empowering all people to to achieve their potential and live meaningful lives.
Visualize data lake address datasets on a map with Amazon Athena and Amazon Location Service geocoding
Many public sector customers in government, healthcare, and life sciences have data lakes that contain addresses (e.g., 123 Main Street). These customers frequently ask how they can quickly visualize these addresses on a geographic map to get a more intuitive understanding of how these addresses are distributed. In this post, learn how to use Amazon Athena and Amazon Location Service to perform ad hoc geocoding on an example dataset and visualize these geocoded addresses on an Amazon QuickSight map.
Visualizing donor data with Amazon QuickSight
Data is an invaluable asset in the world of nonprofits. In this blog post, we offer a technical walkthrough to learn how nonprofits of all sizes can use Amazon QuickSight to quickly create interactive dashboards with the help of machine learning, providing a self-service way to effectively consume and analyze data without writing any code or having to worry about infrastructure.
Rush University Medical Center creates COVID-19 analytics hub on AWS
Rush University Medical Center embraced cloud transformation for internal operations and organizational needs as well as in response to the COVID-19 pandemic. The Rush analytics team worked with the city of Chicago department of public health to create a working reference implementation of a cloud-based public health analytics hub. This hub aggregates, combines, and analyzes multi-hospital data related to patient admissions, discharges and transfers, electronic lab reporting, hospital capacity, and clinical care documents of COVID-19 patients receiving care in and across Chicago hospitals.
How Times Higher Education accelerated their journey with the AWS Data Lab
Times Higher Education (THE) is a data-driven business that, with the help of AWS, is now realising the value of their data, which enables them to be better informed and make faster decisions for customers. THE provides a broad range of services to help set the agenda in higher education, and their insights help universities improve through performance analysis. THE worked with the AWS Data Lab to create a centralised repository of their data. Launching a data lake helped with providing a cost-effective platform and cataloguing data so they could understand their data and design new products to make use of it.
Scaling to share unprecedented volume of election donation data, quickly and cost-effectively
Campaign contributions have grown exponentially in the United States. In 1980, there were around 500,000 contributions made; in 2020 alone, the Federal Election Commission (FEC) expects 500 million contributions. Meanwhile, the evolution of technology has changed the way Americans contribute to political campaigns, making it easier to make many small contributions. To meet unprecedented demand for data transparency, the FEC turned to the cloud.
OSU-OKC upskills its workforce and drives real-time decision making with live reporting and analytical modeling
Oklahoma State University in Oklahoma City (OSU-OKC), a two-year, technical-focused college, has historically faced challenges with consistent reporting, database management, and analytics. Technology generalists hired to do these tasks required extensive training to successfully extract data from traditional student information systems, manipulate data for state and federal compliance reporting, and generate limited campus reporting for operational or academic program review and analysis.